library(nycflights13)
library(tidyverse)

-- Attaching packages --------------------------------------- tidyverse 1.2.1 --
v ggplot2 3.0.0     v purrr   0.2.5
v tibble  1.4.2     v dplyr   0.7.6
v tidyr   0.8.1     v stringr 1.3.1
v readr   1.1.1     v forcats 0.3.0
-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()

flights

# filter by flights on the 1st of january
(jan1 <- filter(flights, month == 1, day == 1))

sqrt(2) ^ 2 == 2

[1] FALSE

1 / 49 * 49 == 1

[1] FALSE

near(sqrt(2) ^ 2, 2)

[1] TRUE

near(1 / 49 * 49, 1)

[1] TRUE

(nov_dec <- filter(flights, month == 11 | month == 12))

# using shorthand
(nov_dec <- filter(flights, month %in% c(11, 12)))

# using demorgan's
(delay_range <- filter(flights, !(arr_delay > 120 | dep_delay > 120)))

NA > 5

[1] NA

10 == NA

[1] NA

NA == NA

[1] NA

x <- NA
is.na(x)

[1] TRUE

df <- tibble(x = c(1, NA, 3))
filter(df, x > 1)

filter(df, is.na(x) | x > 1)

# 1
filter(flights, arr_delay >= 120)

filter(flights, dest == "IAH" | dest == "HOU")

filter(flights, carrier == "UA" | carrier == "AA" | carrier == "DL")

filter(flights, month %in% c(7, 8, 9))

filter(flights, dep_delay <= 0, arr_delay > 120)

filter(flights, dep_delay >= 60, dep_delay - arr_delay > 30)

filter(flights, between(dep_time, 0, 600) | dep_time == 2400)

filter(flights, is.na(dep_time))

arrange(flights, year, month, day)

arrange(flights, desc(dep_delay))

arrange(flights, dep_delay)

# Missing values are always sorted at the end
df <- tibble(x = c(5, 2, NA))
arrange(df, x)

arrange(df, desc(x))

# 1
arrange(flights, desc(is.na(dep_time)), dep_time)

# 2
# Most delayed
arrange(flights, desc(dep_delay))

# Earliest
arrange(flights, dep_delay)

# 3
# total air time
arrange(flights, air_time)

# average air time
arrange(flights, distance / air_time * 60)

# 4
# interpretation 1
arrange(flights, desc(distance))

arrange(flights, distance)

# interpretation 2
arrange(flights, desc(air_time))

arrange(flights, air_time)

select(flights, year, month, day)

# Select range of columns
select(flights, year:day)

# Exclude columns
select(flights, -(year:day))

(renamed <- rename(flights, tail_num = tailnum))

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